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Research ArticleDevelopment and Validation of HPLC Method forthe Simultaneous Determination of Five Food Additivesand Caffeine in Soft Drinks

Bürge AGçJ, Fule Dinç Zor, and Özlem Aksu Dönmez

Department of Chemistry, Faculty of Science and Arts, Yildiz Technical University, Davutpasa, 34220 Istanbul, Turkey

Correspondence should be addressed to Sule Dinc Zor; sule [email protected]

Received 9 December 2015; Revised 19 January 2016; Accepted 20 January 2016

Academic Editor: Josep Esteve-Romero

Copyright © 2016 Burge Ascı et al. This is an open access article distributed under the Creative Commons Attribution License,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Box-Behnken design was applied to optimize high performance liquid chromatography (HPLC) conditions for the simultaneousdetermination of potassium sorbate, sodium benzoate, carmoisine, allura red, ponceau 4R, and caffeine in commercial soft drinks.The experimental variables chosen were pH (6.0–7.0), flow rate (1.0–1.4mL/min), and mobile phase ratio (85–95% acetate buffer).Resolution values of all peak pairs were used as a response. Stationary phase was Inertsil OctaDecylSilane- (ODS-) 3V reversephase column (250 × 4.6mm, 5 𝜇m) dimensions. The detection was performed at 230 nm. Optimal values were found 6.0 pH,1.0mL/min flow rate, and 95% mobile phase ratio for the method which was validated by calculating the linearity (𝑟2 > 0.9962),accuracy (recoveries ≥ 95.75%), precision (intraday variation ≤ 1.923%, interday variation ≤ 1.950%), limits of detection (LODs),and limits of quantification (LOQs) parameters. LODs and LOQs for analytes were in the range of 0.10–0.19 𝜇g/mL and 0.33–0.63 𝜇g/mL, respectively.The proposed method was applied successfully for the simultaneous determination of the mixtures of fivefood additives and caffeine in soft drinks.

1. Introduction

Food additives are widely used in foodstuffs to prevent fromspoilage and improve color, flavor, and texture of foods.However, these additives in foods may affect individuals whoare sensitive with some type of allergy, asthma, and hayfever. Consequently, authorities have set threshold values foracceptable daily intake, varying from country to country. Forinstance, the list of authorised food additives and maximumpermitted levels in European Union are laid down in theannexes of council directive [1, 2].

To ensure food safety from farm to fork, it is also essentialto develop effective and reliable analytical methods for themonitoring of the additive levels in food [3]. Therefore,various analytical methods have been reported for the simul-taneous determination synthetic food additives, such as thinlayer chromatography [4], UV-visible spectrophotometry [5,6], voltammetry [7, 8], differential pulse polarography [9],capillary electrophoresis [10], HPLC-DAD [11–14], HPLC-MS [15], and HPLC-MS-MS [16, 17]. Until now, although

many analytical techniques have been developed for thedetermination of various food additives in foods, there is noreport about simultaneous determination of this combinationin food samples. Among these analytical methods, HPLCcoupled with UV/Vis or diode array detectors (DADs) arethe most commonly used methods due to their sensitivity,selectivity, and high resolution. So, development of effec-tive chromatographic separation method involves judiciousselection of experimental conditions that is suitable for theseparation of interested components at an adequate resolu-tion with reasonable run time. In this regard, experimentaldesign is a useful tool to simplify the laborious work [18].It not only is a timesaving method but also it has an abilityto reveal possible interactions between variables [19, 20].Hence, experimental designs have been increasingly usedto determine the optimum conditions of chromatographicseparation of some analytes in food, drug, and biological fluidsamples with aminimumnumber of experiments for over thepast decade [21–28].

Hindawi Publishing CorporationInternational Journal of Analytical ChemistryVolume 2016, Article ID 2879406, 8 pageshttp://dx.doi.org/10.1155/2016/2879406

2 International Journal of Analytical Chemistry

In this paper, a new RP-HPLC method was developed,using experimental design, for simultaneous determinationof five synthetic food additives in soft drinks, includingthree synthetic colorants (carmoisine, allura red, and pon-ceau 4R), two preservatives (potassium sorbate and sodiumbenzoate), and caffeine. For the optimization procedure, Box-Behnken design (BBD) was used to construct mathematicalmodels that predict how changes input or controlled byvariables (pH, flow rate, and mobile phase ratio) affectedthe resolution in defined experimental region. Further, themethod validation has been carried out according to theInternational Conference on Harmonization guidelines. Theoptimized and validated method was successfully applied tosome commercial soft drinks containing potassium sorbate,sodium benzoate, carmoisine, allura red, ponceau 4R, andcaffeine.

2. Experimental

2.1. Apparatus. Chromatographic analyses were performedusing a Shimadzu HPLC system (Kyoto, Japan) consistingof a model LC20 AT pump unit, SPD-20A UV-Vis detector,7725 20𝜇L sample injection, a computer, and an InertsilOctaDecylSilane- (ODS-) 3V column (5𝜇m, 250mm ×4.6mm; GL Sciences, Tokyo, Japan). The statistical analysisfor the analytical responses and validation data was evaluatedwith Microsoft Excel 2000 software. The statistical softwareStatgraphics Centurion XV (StatPoint Inc., VA, USA) wasused for the graph plotting and for estimating the responsesof experimental variables.

2.2. Chemicals and Reagents. All chemicals and solventswere of analytical reagent grade and used without furtherpurification. Milli-Q water was used to prepare the solu-tions and mobile phases (Millipore, Milford, MA, USA).Sodium acetate trihydrate, glacial acetic acid, and HPLC-grade acetonitrile were acquired from Merck (Darmstadt,Germany). Potassium sorbate (≥99.0% purity), sodium ben-zoate (≥99.0%, purity), carmoisine (≥98.0% purity), allurared (≥98.0% purity), ponceau 4R (≥99.0% purity), andcaffeine (100.0% purity) were purchased from Sigma-Aldrich(St. Louis, Missouri, USA).

2.3. Preparation of Standard Solutions. Standard stock solu-tions of potassium sorbate, sodium benzoate, and caffeinewere prepared at a concentration of 250𝜇g/mL. Standardstock solutions of carmoisine, allura red, and ponceau 4Rwere prepared at a concentration of 100 𝜇g/mL. Fresh work-ing solutions in the concentration range of 2–10𝜇g/mL forcarmoisine, allura red, and ponceau 4R and 5–25 𝜇g/mLfor caffeine, potassium sorbate, and sodium benzoate wereprepared by the dilution of the standard stock solutions inMilli-Q water.

2.4. Sample Preparation. Soft drink samples were purchasedfrom local supermarkets in Istanbul, Turkey, and weredegassed in an ultrasonic bath for 5min. Then, 1mL ofthe sample was transferred to a 10mL volumetric flask anddiluted to the volumewithMilli-Qwater. Prior to the analysis,

Table 1: The experimental variables and levels of BBD.

Variable Level−1 0 +1

pH (𝐴) 6.0 6.5 7.0Flow rate (𝐵) (mLmin−1) 1.0 1.2 1.4Mobile phase ratio (𝐶) (%) 85 90 95

both soft drink samples and standard solutions were filteredthrough 0.45 𝜇m Millipore filters and then injected intoHPLC system.

2.5. Chromatographic Procedure. The optimum separation ofall analytes was achieved with 0.025M sodium acetate/aceticacid buffer, pH 6.0, acetonitrile gradient that follows 0–5min,95 : 75 (v/v); 5–10min, 70 : 30 (v/v). The mobile phase flowrate was 1.0mL/min and the injection volume was 20𝜇L inall the chromatographic runs.The detection was made with avariable ultraviolet-visible detector fixed at 230 nm.

2.6. Optimization Procedure. A Box-Behnken design (BBD)using three variables at three levels (coded levels: −1, 0,and +1) was used for the optimization of simultaneousdetermination of potassium sorbate, sodium benzoate, car-moisine, allura red, ponceau 4R, and caffeine by HPLC. Thisdesign was selected due to the small number of experimentsrequired. The variables and levels selected for optimizationprocedure were pH (𝐴; 6.0, 6.5, and 7.0), flow rate (𝐵; 1.0, 1.2,and 1.4), and mobile phase ratio (in terms of acetate buffer)(𝐶; 85, 90, and 95) (Table 1). The proposed HPLC methodanalyzed the compounds in two steps as mentioned above.While the first step has an effect on the chromatographicseparation, the second step has an effect on the run timeof the method. Therefore, experimental variables of thefirst step of HPLC method were taken into account. 15experimental runs were performed at random and overallresolution (𝑅) was chosen as the response for the separationof the compounds [19]. Experimental designmatrix used andthe results obtained by BBD were listed in Table 2.

2.7. Validation Procedure. In-house validation of the methodwas performed according to International Conference onHarmonization guidelines (ICH Q2R1) [29]. Evaluatedparameters are linearity of calibration curve, limit of detec-tion (LOD), limit of quantification (LOQ), and precision,accuracy, and stability. The linearity of the HPLC methodfor the determination of five food additives and caffeinewas evaluated in a concentration range of 2–10𝜇g/mL forcarmoisine, allura red, and ponceau 4R and 5–25𝜇g/mL forpotassium sorbate, sodium benzoate, and caffeine coveringthe normal range of concentrations obtained when analyzingsoft drinks. Calibration equations were calculated by the leastsquares treatment of the peak area of the food additivesand caffeine. The limit of detection (LOD) and limit ofquantitation (LOQ) were calculated as LOD 3𝑥𝜎/𝑆 and LOQ10𝑥𝜎/𝑆, where 𝜎 is the standard deviation of intercept and 𝑆is the slope. In order to test the prediction performance of theproposed methods, intraday (three times in a day operation

International Journal of Analytical Chemistry 3

Table 2: Experimental design matrix and the responses for BBD.

Run 𝐴 𝐵 𝐶 𝑅

1 6.0 1.0 90 1.0412 7.0 1.0 90 0.6223 6.0 1.4 90 0.5534 7.0 1.4 90 0.1285 6.0 1.2 85 0.0006 7.0 1.2 85 0.0277 6.0 1.2 95 3175.3738 7.0 1.2 95 1792.2079 6.5 1.0 85 0.04610 6.5 1.4 85 0.00011 6.5 1.0 95 2487.82312 6.5 1.4 95 1257.45513 6.5 1.2 90 0.75914 6.5 1.2 90 0.32715 6.5 1.2 90 0.918

under the same conditions) and interday (four different days)studies were performed at three different concentrations(Level 1: 10 𝜇g/mL; Level 2: 15 𝜇g/mL; Level 3: 20𝜇g/mL forpotassium sorbate, sodium benzoate, and caffeine; Level 1:4 𝜇g/mL; Level 2: 6 𝜇g/mL; Level 3: 8 𝜇g/mL for carmoisine,allura red, and ponceau 4R). Accuracy of the method wasascertained by a recovery study by adding a known amountof reference standards to the soft drink samples. Firstly,0.5mL of the soft drink sample was transferred to a 10mLvolumetric flask and the reference standards were added onit at three different concentration levels.Then, added sampleswere diluted to the volume with Milli-Q water, filtered, andanalyzed.

3. Results and Discussion

3.1. Optimization of the HPLC Method. Chromatographicoptimization requires selecting suitable criteria for the eval-uation of the resultant chromatograms in order to choosethe optimum conditions. BBD is an independent, rotatable,or nearly rotatable second-order design based on three-levelincomplete factorial designs. It is more efficient comparedto other response surface designs, such as central compositedesigns. It can also provide sufficient information to testthe lack of fit, and therefore it is one of the best quadraticmodels for response surface method and has been widelyused in analytical fields. Because of the nonlinearity of themodel, a polynomial function to contain second-ordermodelis postulated to describe the evolution phenomenon:

𝑦𝑖= 𝑏0+

𝑛

∑

𝑖=1

𝑏𝑖𝑥𝑖+

𝑛

∑

𝑖=1

𝑏𝑖𝑖𝑥2

𝑖+

𝑛

∑

1≤𝑖≤𝑗

𝑏𝑖𝑗𝑥𝑖𝑥𝑗+ 𝜀𝑖, (1)

where 𝑛 is the number of variables, 𝑏0is the constant term, 𝑏

𝑖,

𝑏𝑖𝑖, and 𝑏

𝑖𝑗represent the coefficient of the first-order terms,

quadratic terms, and interaction terms, respectively, and 𝜀𝑖

is a term that represents other sources of variability notaccounted for the estimation, such as background noise [30].

Table 3: ANOVA results for optimization by BBD.

Effect SS D.f. MS 𝐹-ratio 𝑃 value𝐴 239422 1 239422 1.95 0.2216𝐵 189543 1 189543 1.54 0.2694𝐶 9489050 1 9489050 77.20 0.0003∗

𝐴𝐴 86144 1 86144 0.70 0.4407𝐴𝐵 0 1 0 0.00 1.0000𝐴𝐶 478304 1 478304 3.89 0.1056𝐵𝐵 86239 1 86239 0.70 0.4404𝐵𝐶 378422 1 378422 3.08 0.1397𝐶𝐶 4374670 1 4374670 35.59 0.0019∗

Total error 614539 5 122908Total (corr.) 15999393 14SS: sum of squares; MS: mean squares; 𝐹-ratio: MS/MSerror; 𝑃 value:probability level; D.f.: degree of freedom.𝑅2= 0.961, 𝑅2 (adjusted for D.f.) = 0.892.

∗Significant factor at 𝛼 = 0.05.

A B C

−1.0 1.0 −1.0 1.0 −1.0 1.0−400

100

600

1100

1600

2100

2600

R

Figure 1: Analysis of the main variables in BBD.

The experimental results are shown in Table 2. Theregressionmodel for the response was tested through analysisof variance (ANOVA). From the results of ANOVA (Table 3),it can be deduced that linear contribution of mobile phaseratio (𝐶) and quadratic contribution of mobile phase ratio(𝐶𝐶) influence the resolution significantly. Interactions ofthe individual variables in this study are not significantto resolution in the selected range. Fitted quadratic modelequation is also presented in (2). Figure 1 shows the analysisof individual variables of experimental design. From Figure 1,it can be seen how the value of the resolution may increase ifwe take higher mobile phase ratio (𝐶). Also, we can infer thatalthough pH (𝐴) and flow rate (𝐵) do not greatly influencethe resolution better resolutions are obtained for low valuesof pH and flow rate

�� = 0.67 − 172.99𝐴 − 153.92𝐵 + 1089.10𝐶

+ 152.74𝐴2− 345.80𝐴𝐶 − 152.83𝐵

2− 307.58𝐵𝐶

+ 1088.49𝐶2.

(2)

The regression models obtained were used to calculatethe response surface for each variable separately. Figure 2illustrates the response surface plots for the resolutions. In


Table 4:The important parameters of the calibration equations for the proposedHPLCmethod for simultaneous determination of potassiumsorbate (SOR), sodium benzoate (BEN), carmoisine (CAR), allura red (ALU), ponceau 4R (PON), and caffeine (CAF).

Compounds Calibration range(𝜇g/mL)

Regression equation(𝑌 = 𝑎𝑋 + 𝑏) 𝑆

𝑎𝑆𝑏

𝑟2 LOD

(𝜇g/mL)LOQ

(𝜇g/mL)SOR 5–25 𝑌 = 7.8097 × 104𝑋 + 4.6484 × 104 1.391 × 103 2.3076 × 104 0.9990 0.12 0.40BEN 5–25 𝑌 = 3.3313 × 104𝑋 + 1.2421 × 104 7.52 × 102 1.2469 × 104 0.9985 0.10 0.33CAR 2–10 𝑌 = 4.3383 × 104𝑋 + 1.8834 × 104 6.86 × 102 4.555 × 103 0.9992 0.16 0.53ALU 2–10 𝑌 = 5.5741 × 104𝑋 − 7.427 × 103 9.22 × 102 1.5292 × 104 0.9992 0.11 0.35PON 2–10 𝑌 = 6.043 × 103𝑋 + 5.0389 × 104 2.150 × 103 1.4264 × 104 0.9962 0.17 0.56CAF 5–25 𝑌 = 2.4885 × 104𝑋 + 4.6613 × 104 4.81 × 102 3.1891 × 104 0.9989 0.19 0.63𝑌: peak area;𝑋: concentration (𝜇g/mL); 𝑆𝑎: standard deviation of the slope; 𝑆𝑏: standard deviation of the intercept.

−1 −0.6 −0.2 0.2 0.6 1A

−1 −0.20.6B

−400600

160026003600

R

(a)

−1 −0.6 −0.2 0.2 0.6 1A

−1 −0.20.6C

−500500

150025003500

R

(b)

−1 −0.6 −0.2 0.2 0.6 1B

−1−0.2

0.6C

−400600

160026003600

R

(c)

Figure 2: Response surface plots for BBD: (a) pH (𝐴) versus flow rate (𝐵) (mobile phase ratio: 95%); (b) pH (𝐴) versus mobile phase ratio(𝐶) (flow rate: 1.0mL/min); (c) flow rate (𝐵) versus mobile phase ratio (𝐶) (pH: 6.0).

particular, the effect of pH (𝐴) and mobile phase ratio (𝐶)on resolution is shown in Figure 2(b). This plot shows thatthe highest resolution is obtained at greater values of themobile phase ratio. The relation between the effects of theother variables on the resolution is also plotted in Figures2(a)–2(c).

According to the results of the optimization proce-dure, the optimum variables corresponded to pH, 6.0; flowrate, 1.0mL/min; mobile phase ratio, 95%. A typical chro-matogram obtained under optimum conditions is shown inFigure 3.

3.2. Validation of the HPLC Method. The results of thelinearity, LODs, andLOQs are summarized inTable 4.A goodlinear relationship is displayed between the correspondingpeak areas and the concentrations of the compounds basedon the correlation coefficients (𝑟2 > 0.9962). The LODs ofthe six compounds were in the range of 0.10–0.19 𝜇g/mL, andthe LOQs of the six compounds were in the range of 0.33–0.63 𝜇g/mL. So, these values demonstrated that the proposed

1 2 3 4

5

6

(min)9.08.07.06.05.04.03.02.01.00.0

Detector A: 230nm400

350

300

250

200

150

100

50

0

(mV

)

Figure 3: Chromatogram of synthetic standard mixture containingfive food additives and caffeine recorded under optimized analysisconditions (1: sodium benzoate (15𝜇g/mL), 2: potassium sorbate(15𝜇g/mL), 3: caffeine (15 𝜇g/mL), 4: ponceau 4R (6 𝜇g/mL), 5: allurared (6 𝜇g/mL), and 6: carmoisine (6 𝜇g/mL)).

analytical method was sufficiently sensitive. A summary ofintraday (the RSD of the recoveries of the nine samples) and


Table5:Va

lidationof

thes

imultaneou

sdeterminationof

food

additiv

esandcaffeineb

ydevelop

edmetho

dpo

tassium

sorbate(SO

R),sod

ium

benzoate(BEN

),carm

oisin

e(CA

R),allu

rared

(ALU

),po

nceau4R

(PON),andcaffeine(CA

F).

Levels

SOR(𝜇g/mL)

BEN(𝜇g/mL)

CAR(𝜇g/mL)

ALU

(𝜇g/mL)

PON(𝜇g/mL)

CAF(𝜇g/mL)

10.0

15.0

20.0

10.0

15.0

20.0

4.0

6.0

8.0

4.0

6.0

8.0

4.0

6.0

8.0

10.0

15.0

20.0

Intra-assay

9.97

15.22

19.76

9.70

15.37

20.18

4.05

6.17

7.92

3.90

6.02

7.86

3.79

5.72

7.75

9.96

15.15

20.28

9.80

15.30

20.01

10.02

15.09

20.21

4.15

6.33

8.01

3.83

5.97

7.82

3.89

5.92

7.91

9.99

15.50

20.02

9.91

15.31

19.86

10.03

14.79

20.38

4.18

6.20

8.11

3.87

6.06

7.70

3.92

5.87

8.04

10.03

15.16

20.20

Mean

9.89

15.28

19.88

9.92

15.08

20.26

4.13

6.23

8.01

3.87

6.02

7.79

3.87

5.84

7.91

9.99

15.27

20.16

RSD

a %0.869

0.321

0.634

1.895

1.923

0.533

1.646

1.364

1.186

0.904

0.747

1.060

1.757

1.781

1.643

0.350

0.310

0.689

Recovery%

98.90

101.8

799.40

99.20

100.53

101.3

0103.25

103.83

100.13

96.75

100.33

97.83

96.75

97.33

98.88

99.90

101.8

0100.80

Interassay

9.92

15.09

19.66

9.84

14.76

20.71

4.14

6.01

7.81

3.91

6.01

7.96

4.10

6.01

8.20

10.35

15.10

20.09

9.84

15.23

19.59

9.85

14.95

20.74

4.18

6.06

8.14

3.85

5.84

7.90

4.08

6.18

8.26

10.01

15.32

20.43

9.77

15.21

19.69

9.81

14.79

20.25

4.05

6.19

7.96

3.81

5.86

8.04

3.83

6.20

8.24

10.17

14.88

20.07

9.68

15.40

19.89

10.02

14.82

20.11

4.19

6.22

7.98

3.76

6.08

7.82

4.01

5.98

7.99

10.03

15.16

20.20

Mean

9.80

15.23

19.71

9.88

14.83

20.45

4.14

6.12

7.97

3.83

5.95

7.93

4.03

6.09

8.14

10.14

15.11

20.20

RSD%

1.041

0.840

0.624

0.961

0.566

1.565

1.546

1.650

1.694

1.644

1.950

1.173

1.919

1.855

1.518

1.548

1.204

0.817

Recovery%

98.00

101.5

398.55

98.80

98.87

102.25

103.50

102.00

99.62

95.75

99.17

99.13

100.75

101.5

0102.12

101.4

0100.73

101.0

0a R

elatives

tand

arddeviation,

RSD(%

),standard

deviation/mean×100.


Table 6: Results of accuracy studies (mean value ± standard deviation, 𝑛 = 5).

Sample Food additive Sample concentration (𝜇g/mL) Added (𝜇g/mL) Found (𝜇g/mL) Recovery (%)

Energy drink

Potassium sorbate 10.683 13.70 ± 0.048 100.676 16.90 ± 0.057 103.679 20.00 ± 0.065 103.56

Caffeine 7.113 10.18 ± 0.045 102.336 13.25 ± 0.054 102.339 16.61 ± 0.042 105.56

Allura red 3.261 4.31 ± 0.038 105.002 5.34 ± 0.037 104.003 6.39 ± 0.044 104.33

Pomegranate juice

Potassium sorbate 12.713 15.64 ± 0.059 97.676 18.61 ± 0.103 98.339 21.74 ± 0.166 100.34

Sodium benzoate 7.243 10.34 ± 0.040 103.606 13.30 ± 0.054 101.209 16.45 ± 0.063 102.50

Carmoisine 1.211 2.25 ± 0.012 104.002 3.30 ± 0.017 104.503 4.34 ± 0.022 104.40

Ponceau 4R 4.081 5.11 ± 0.036 102.662 6.16 ± 0.039 104.163 7.15 ± 0.045 102.22

interday precision (the RSD of the recoveries of the twelvesamples) are listed in Table 5. The RSD values ranged from0.310% to 1.950% for the HPLC method. These results showthat the proposed method is precise for the simultaneousdetermination of these compounds. The recoveries of the sixcompounds to determine the accuracy of the method aresummarized in Table 6. The proposed method resulted insatisfactory recoveries for all additives and caffeine, rangingfrom97.67% to 105.56%.The recoveries demonstrated that thematrixes have negligible effect on the quantification of thesecompounds and the method is accurate within the desiredrange. Under refrigerated and room temperature conditions,all food additives and caffeine inmobile phase andwater werestable for at least 1 month.

These results show that the proposed method is precise,accurate, and sensitive for the simultaneous determination ofthe six compounds and can be used for routine analysis ofpotassium sorbate, sodium benzoate, carmoisine, allura red,ponceau 4R, and caffeine in soft drinks.

3.3. Application of the Method. The proposed HPLC methodwas applied to the simultaneous determination of potassiumsorbate, sodium benzoate, carmoisine, allura red, ponceau4R, and caffeine in different soft drinks. Five replicatesdetermination was made and the results are summarized inTable 7. The concentration of food additives in soft drinksranged from 24.26 ± 0.47 𝜇g/mL to 254.13 ± 1.24 𝜇g/mL.The amounts of food additives and caffeine in all soft drinksamples were below the limit value defined in the legislationon the food additives [1, 2].

Table 7: Analysis of soft drinks (mean value ± standard deviation,𝑛 = 5).

Food additive Energy drink(𝜇g/mL)

Pomegranatejuice

(𝜇g/mL)

Mandarinjuice

(𝜇g/mL)Potassium sorbate 213.62 ± 0.34 254.13 ± 1.24 246.23 ± 1.76Sodium benzoate — 144.71 ± 2.38 148.67 ± 1.99Caffeine 142.20 ± 1.17 — —Allura red 65.28 ± 0.59 — —Carmoisine — 24.26 ± 0.47 —Ponceau 4R — 81.58 ± 1.51 —

4. Conclusion

An efficient, accurate, and reliable method for the simulta-neous determination of five food additives and caffeine insoft drinks was developed using HPLC. Box-Behnken designwas applied to the optimization of the chromatographic sep-aration conditions and this design reduced to the number ofexperiments required. It can be concluded that a slight changein mobile phase ratio has a direct effect on the resolution. Allthe validation parameters were within the acceptance range.High percentage recovery data also shows that the proposedmethod is free from the interference. Consequently, this studywill provide a sensitive and rapid method for the detection ofpotassium sorbate, sodium benzoate, carmoisine, allura red,ponceau 4R, and caffeine in soft drinks.


Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper.

Acknowledgment

This work was financially supported by Yildiz Technical Uni-versity Research Foundation (Project no. 2010-01-01-GEP04).

References

[1] Regulation (EC) no 1333/2008 of the European Parliament andof the Council on Food Additives, 2008.

[2] European Commission, Commission Directive 2008/84/EC,Laying down Specific Purity Criteria on Food Additives OtherThan Colours and Sweeteners, 2008.

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